Evidence map›Paper›PMID 40973961›Full record

ArticleBMC cancer2025

Highly-accurate prediction of colorectal cancer through low abundance uncultivated genomes recovered using metagenomic co-assembly and binning approach.

Po-Ting Lin, Yu-Wei Wu

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Article in BMC cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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2 authors.

Po-Ting LinDepartment of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei, 10607, Taiwan.
Yu-Wei WuGraduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, 250, Wuxing St., Sinyi District, Taipei, 11031, Taiwan. yuwei.wu@tmu.edu.tw.ORCID http://orcid.org/0000-0002-5603-1194

Funding

Ministry of Science and Technology, Taiwan MOST110-2221-E-038-019-MY3Ministry of Science and Technology, Taiwan MOST111-2221-E-038-023-MY3Taipei Medical University-National Taiwan University of Science and Technology Joint Research Program grant TMU-NTUST-108-08
6 · The paper itself

Abstract

backgroundRecent microbiome studies have established the association between the composition of gut microbiota and various diseases. Since 16S ribosomal RNA sequencing may suffer from problems such as lower taxonomic resolution or limited sensitivity, more and more studies embraced whole-metagenome approach, which has the potential of sequencing everything in the target microbiome, to conduct microbial association analysis. However, species profiling, which is the most popular analysis technique for whole-metagenome analysis, cannot detect uncultivated species. Since uncultivated species may also be indispensable in the gut environments, it is crucial to identify those uncultivated species and evaluate their importance in discerning disease samples from healthy ones.

resultsAfter conducting de novo co-assembly and genome binning procedures on two colorectal cancer (CRC) cohorts, in which one of them was from the Asian population while the other was from the Caucasian population, we identified that the Asian and Caucasian cohorts shared a significant amount of microbial species in their microbiota. In addition we found that low abundance genomes may be more important in classifying disease and healthy metagenomes. By sorting the genomes based on their random forest importance scores in differentiating disease and healthy samples and cumulatively evaluating the genome subsets in predicting CRC status, we identified dozens of "important" genomes for each of the cohorts that were able to predict CRC with very high accuracy (0.90 and 0.98 AUROC for the Asian and Caucasian cohorts respectively). Uncultivated species were also identified among the selected genomes, highlighting the importance of including the uncultivated species in order to build better disease prediction models and evaluate the roles of the uncultivated species in the disease formation or progression. Finally we found that the "important" species for both cohorts did not overlap with each other, hinting that the species highly associated with CRC disease may be different between the Eastern and Western populations.

conclusionIn this study we demonstrated the importance of recovering and analyzing low abundance uncultivated species to identify their associations with colorectal cancer. We hope this work shed new light on a more comprehensive understanding of how our gut microbes are correlated with diseases.

Indexed as

Colorectal NeoplasmsGastrointestinal MicrobiomeMetagenomicsAsian PeopleFemaleHumansMaleMetagenomeRNA, Ribosomal, 16SWhite PeopleRNA, Ribosomal, 16SBinningCo-assemblyColorectal cancerMetagenome-assembled genomeRandom forest feature importanceUncultivated species

Identifiers

PMID40973961
PMCPMC12449802

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.